CS180 Computer Vision Project

This repository contains the implementation of our Computer Vision project for CS 180: Artificial Intelligence, a course under the Department of Computer Science, College of Engineering, University of the Philippines, Diliman. Developed under the guidance of Associate Professor Carlo Raquel, this project was completed during the academic year 2024-2025.

Team Members

• Andres, Lance Leo
• Chio, Mikhail Anton B.
• Tuan, Hamdi

How to Run the Project

Step 1: Clone the Repository

git clone git@github.com:antonbc/cs180-project.git

Step 2: Navigate to the Project Directory

cd cs180-project

Step 3: Download Pre-Trained Models

Download the required pre-trained models from this Google Drive Link of Pre-Trained Models

Step 4: Place Downloaded Pre-Trained Models in Project Directory

After Downloading CNN_transfer_learning/ and VIT_transfer_learning/ add them to the project directory.

Step 5: Install Required Dependencies for the Model

pip install numpy matplotlib torch torchvision tensorboard timm pandas openpyxl

Step 6: Open Jupyter Notebook and Run the Demo Notebook

jupyter notebook Demo+predictions.ipynb

Code Structure

• outputs/: Contains the outputs of each model.
• train/: Contains the training set for both models.
• test/: Contains the test set for both models.
• training_results/: Contains the accuracy graphs of each model used.
• CNN_train.ipynb: Contains the solution for deep learning-based approaches that do not employ transformer architectures.
• VIT_train.ipynb: Contains the solution for deep learning-based approaches underpinned by transformer architectures.
• Demo+predictions.ipynb: Contains our Demo Model which contains both the VIT model and CNN model.